ml.core.state

Defines a dataclass for keeping track of the current training state.

ml.core.state.set_phase(model: Module, phase: Literal['train', 'valid', 'test']) → tuple[Module, Literal['train', 'valid', 'test']][source]

ml.core.state.cast_phase(raw_phase: str) → Literal['train', 'valid', 'test'][source]

class ml.core.state.State(num_epochs: int = '???', num_steps: int = '???', num_epoch_steps: int = '???', num_samples: int = '???', num_epoch_samples: int = '???', num_valid_steps: int = '???', num_test_steps: int = '???', start_time_s: float = '???', elapsed_time_s: float = '???', raw_phase: str = '???')[source]

Bases: object

num_epochs: int = '???'

num_steps: int = '???'

num_epoch_steps: int = '???'

num_samples: int = '???'

num_epoch_samples: int = '???'

num_valid_steps: int = '???'

num_test_steps: int = '???'

start_time_s: float = '???'

elapsed_time_s: float = '???'

raw_phase: str = '???'

property phase: Literal['train', 'valid', 'test']

classmethod init_state() → State[source]

property training: bool

num_phase_steps(phase: Literal['train', 'valid', 'test']) → int[source]